Package index • aphantasiaCognitiveClustering

R objects

study_data: Study data retrieved from the OSF project

models_list: Models for all the variables predicted by Groups, Clusters and Sub-clusters

Data manipulation

filter_study_variables(): Filter the Variable column of a long format data frame

format_association_table(): Display the association table for a specific variable in a clean format

get_longer(): Transform the main data frame to long format

merge_clusters(): Add the clustering and reduced variables to the main data frame

scale_vars(): Scale original quantitative variables to a defined range

scale_reduce_vars(): Reduce the number of variables to prepare for clustering

Modelling

cluster_selected_vars(): Use Gaussian Mixture Models to cluster selected variables

fit_stan_glm(): Fit a stan_glm model with predefined parameters

get_association_models(): Fit and report Bayes Factors for associations with education, fields and occupations

get_bf_inclusion(): Compute Bayes Factor for Inclusion for the groups and age covariate

get_contrast_bf(): Get contrasts between groups in a Bayesian model

get_full_model_table(): Create a table summarising the models for each variable

get_mean_sd(): Get the mean and standard deviation of a variable in a clean table

correlate_vars(): Correlate the original variables with a chosen method and correction

Plotting

add_significance_geoms(): Add significance label and line to a plot

plot_clusters_bic(): Plot the comparison of Gaussian Mixture Models (GMM) BIC scores

plot_score_cor_graph(): Plot a correlation graph

plot_score_cor_joint(): Create a joint matrix + graph correlation figure

plot_score_cor_matrix(): Plot a correlation matrix

plot_score_radars(): Plot scaled score variables as radar charts

plot_score_violins(): Plot the study variables' distributions as half-violins with point averages and error bars.

save_ggplot(): Custom ggsave wrapper set with Nature's formatting guidelines (width-locked)